Launch HN: Inconvo (YC S23) – AI agents for customer-facing analytics

Hi HN, we are Liam and Eoghan of Inconvo (https://inconvo.com https://inconvo.com), a platform that makes it easy to build and deploy AI analytics agents into your SaaS products, so your customers can quickly interact with their data. There’s a demo video at https://www.youtube.com/watch?v=4wlZL3XGWTQ https://www.youtube.com/watch?v=4wlZL3XGWTQ and a live demo at https://demo.inconvo.ai/ https://demo.inconvo.ai/ (no signup required). Docs are at https://inconvo.com/docs https://inconvo.com/docs. SaaS products typically offer dashboards and reports, which work for high-level metrics but are clunky for drill-downs and slow for ad-hoc questions. Modern users, shaped by tools like ChatGPT, now expect a similar degree of speed and flexibility when getting insights from their data. To meet these expectations, you need an AI analytics agent, but these are painful to develop and manage. Inconvo is a platform built from the ground up for developers building AI agents for customer-facing analytics. We make it simple to expose data to Inconvo by connecting to SQL databases. We offer a semantic model to create a layer that governs data access and defines business logic, conversation logs to track user interactions, and a developer-friendly API for easy integration. For observability we show a trace for each agent response to make agent behaviour easily debuggable. We didn’t start out building Inconvo, initially we built a developer productivity SaaS from which we pivoted. Our favourite feature of that product was its analytics agent, and we knew that building one was a big enough problem to solve on its own so we decided to build a developer tool to do so. Our API is designed for multi-tenant databases, allowing you to pass session information as context. This instructs the agent to only analyse data relevant to the specific tenant making the request. Most of our competitors are BI tools primarily designed for internal analytics with limited embedding options through iFrame or unintuitive APIs. If you’re concerned about AI SQL generation, we are too. In our opinion, AI agents for customer-facing analytics shouldn’t generate and run raw SQL without validation. Instead, our agents generate structured query objects that are programmatically validated to guarantee they request only the data allowed within the context of the request. Then we send validated objects to our QueryEngine which converts the object to SQL. With this approach we ensure a bounded set of possible SQL that can be generated, which stops the agent from hallucinating and running rouge queries. Our pricing is upfront and available on our website. You can try the platform for free without a credit card. If you want to try out the full product, you can sign up for free at https://auth.inconvo.ai/en/signup https://auth.inconvo.ai/en/signup. As mentioned, our sandbox demo is at https://demo.inconvo.ai/ https://demo.inconvo.ai/, and there’s a video at https://youtu.be/4wlZL3XGWTQ https://youtu.be/4wlZL3XGWTQ. We're really interested in any feedback you have so please share your thoughts and ideas in the comments, as we aim to make this tool as developer-friendly as possible. Thanks!